LLM Agent

LLM agents are autonomous systems that combine large language models with the ability to interact with their environment, achieving complex tasks through planning, tool use, and iterative refinement. Current research focuses on improving their reliability and safety, including aligning their behavior with human values, enhancing their decision-making processes (e.g., through Q-value models and tree search algorithms), and mitigating vulnerabilities to adversarial attacks. This field is significant because it bridges the gap between theoretical AI and practical applications, impacting diverse areas such as game development, software testing, healthcare, and financial markets by automating tasks and improving decision-making.